This invention relates to both a method and apparatus (as illustrated in FIG. 1) for, particularly, the noninvasive determination of those parameters currently reported on a standard clinical arterial blood gas report. The parameters typically reported are hydrogen ion concentration (pH) partial pressure of carbon dioxide (PCO.sub.2), partial pressure of oxygen (PO.sub.2), bicarbonate concentration ([HCO.sub.3.sup.- ]) and oxygen saturation (O.sub.2 sat.).
Arterial blood gas determination is the cornerstone of diagnosis and management of cardiopulmonary disease in the critically ill patient. As effective oxygenation and maintenance of acid-base balance in such a patient is necessary for survival, measurement of arterial blood gases is typically the most frequently ordered laboratory test in a hospital's intensive care unit. In a patient with respiratory failure, the physician uses the results of blood gas analysis to optimize such a patient's oxygenation and acid-base status. Specifically, decisions regarding oxygen administration, titration of positive end expiratory pressure (PEEP) and minute ventilation are made, at least in part, on the results of arterial blood gas analysis. Repeated determinations are made over time to monitor the progression or remission of cardiopulmonary pathophysiology and to guide efforts at weaning patients from mechanical ventilatory support.
The standard arterial blood gas report contains the following information: pH, PCO.sub.2, PO.sub.2, [HCO.sub.3.sup.- ], and O.sub.2 saturation. The pH and PCO.sub.2 provide valuable information regarding acid-base and ventilation status. The bicarbonate level provides additional information on acid-base balance which allows the physician to determine whether an acid-base abnormality is respiratory or metabolic in origin. The two other indices, PO.sub.2 and O.sub.2 saturation, reflect the amount of oxygen present in the patient's blood.
At the present time standard clinical practice requires arterial puncture for procurement of an arterial blood sample. The arterial puncture is painful to the patient and associated with a variety of complications. Minor complications include arteriospasm, localized internal bleeding (i.e. hematoma), transient occlusion of the artery and temporary loss of sensation in the distribution of the median nerve. Major complications are infrequent, but include hemorrhage and severe vascular occlusion secondary to intraluminal clot formation. On rare occasions, gangrene has necessitated the amputation of a finger or a hand. When multiple samples are required over a relatively short period of time, an indwelling arterial catheter may be useful, the insertion of which can also be painful and which has complications such as described above. Although a standard indwelling arterial catheter allows for repeated sampling, it does not allow for continuous arterial blood gas monitoring.
The necessity, as well as associated complications, of blood gas monitoring are also present when monitoring infants, especially premature infants. The ventilation of premature infants is especially difficult due the immaturity of their lungs. Thus, to optimize the infants chances for survival, the pediatrician or neonatologist must obtain multiple arterial blood gas determinations. Arterial puncture for procurement of the required arterial sample from an infant is typically more difficult than in adults due to the smaller size of the arteries.
In addition to the foregoing, the process for analyzing the arterial blood sample is lengthy, requires multiple personnel and is not continuous. Immediately after withdrawal, the arterial blood sample is placed on ice to inhibit red blood cell metabolism, which metabolism would alter the sample's blood gas parameters and lead to an incorrect measurement of the patients blood gas values. The sample is then transported to the clinical chemistry laboratory in the hospital where it is logged in. Next, the sample is then analyzed by conventional electrochemical techniques. Finally, the results are entered in the hospital computer and made available to the physician for interpretation.
Due to the important clinical role of the information obtained by arterial blood gas analysis in the management of critically ill patients and the drawbacks of conventional clinical analysis, a number of alternative technologies have been proposed to measure one or more blood gas parameters. The prior art is quite diverse but can be divided into 7 major categories.
1. Invasive colorimetric technologies requiring direct contact between the colorimetric substances and arterial blood. These technologies measure pH, PO.sub.2, and PCO.sub.2.
2. Separation of the blood gases by semipermeable membranes, with subsequent concentration determination by absorption spectroscopy. The technology is limited to the measurement of PO.sub.2, and PCO.sub.2.
3. Electrode devices for measurement of PO.sub.2, and PCO.sub.2 in peripheral skin. This technology has been commercially developed by Radiometer, Denmark.
4. Invasive transistor devices for measurement of pH, and PCO.sub.2 in blood.
5. Semi-invasive techniques for measurement of pH, PCO.sub.2 and PO.sub.2 in peripheral skin.
6. Optical or spectroscopic determination of PCO.sub.2 and PCO (partial pressure of carbon monoxide) in tissue;
7. Pulse oximeters for noninvasive measurement of arterial blood oxygen saturation (O.sub.2 sat.).
The terminology used in clinical medicine, technical publications and the prior art patents is not always consistent. In the clinical practice of medicine the term "blood gas" is specific for the determination of certain factors in arterial blood. The determination of blood gases in venous blood is of little or no clinical significance and is not standard practice. Technically the term "blood gas" is misleading as not all of the components listed on a standard laboratory blood gas report are specific for gas measurements. PH and [HCO.sub.3.sup.- ] are concentration measurements of non-gaseous substances. In this application "blood gas parameters" are pH, PCO.sub.2, PO.sub.2, or [HCO.sub.3.sup.- ] and O.sub.2 saturation.
The foregoing parameters are not always measured in arterial blood; they can be measured in tissue and skin. Thus, it is important to distinguish between measurement in arterial blood, tissue and peripheral skin, as their sensitivity and clinical utility differ. Blood gas measurements in arterial blood are currently the reference standard used in clinical medicine and the associated body of knowledge on how to interpret the results is extensive. Additionally there is a minimal time delay between a change in cardiopulmonary status and a corresponding change in arterial blood concentrations.
Several prior art methodologies measure certain blood gas parameters in the peripheral skin or tissue. Peripheral skin and tissue are differentiated in that skin is the outermost layer of the body, while tissue refers to the sum total of body mass existing between two skin surfaces. Thus, a tissue measurement will contain information on the dermal and epidermal layers of the skin, muscle, bond, fat, blood vessels and capillaries. Tissue measurements, if accurate, may be the measurements of highest clinical utility as such measurements define the acid-base and oxygen status of the peripheral tissue. The maintenance of normal physiology in these tissues is the goal when treating cardiopulmonary disease. However, as current clinical instrumentation does not measure tissue blood gas parameters, the practicing physician will be unfamiliar in how to interpret these measurements. Additionally there may be a longer time delay between changes in cardiopulmonary status and a corresponding change in the tissue.
Measurement of blood gas parameters in peripheral skin has limited clinical utility. When peripheral skin measurements are compared to arterial blood measurements, it has been found that the skin measurements of PO.sub.2 are not adequate unless local hyperemia of the skin to facilitate oxygen diffusion is achieved. Peripheral skin measurements are also less sensitive to acute changes in blood gas concentrations. Peripheral skin measurements have so far proven reliable only in babies. In adults, the major difficulty relates to the thickness and permeability of the skin.
To summarize, there are five blood gas parameters which can be determined in three different media, (1) arterial blood, (2) tissue, and (3) peripheral skin. A ranking of the current clinical utility of these measurements would be arterial blood, tissue and peripheral skin a distant third.
Invasive Colorimetric Technologies
While the list of patents and papers describing colorimetric measurement techniques and applications is quite extensive, the application of such technology to the measurement of pH, PCO.sub.2 and PO.sub.2 is well summarized by the following paper and three patents.
U.S. Pat. No. 4,854,321 titled "Integrated Optical System for Monitoring Blood Gases" by A. A. Boiarski describes the use of colorimetric substances in dye wells. A colorimetric substance is a chemical which changes color in a quantifiable way when exposed to another given substance. Litmus paper (e.g. phenolphthalein solution) for measuring pH is a well known example. As stated in the Abstract, "Blood gases . . . are monitored by a single probe having multiple dye wells and dyes immobilized in the wells, the dyes being exposed to the blood gases. Optical fibers and waveguides connected to the dye wells permit light to be directed form a light source to the dyes and the light due to absorption or the spontaneous emission of the dye returned to a light detector. The intensity, phase shift or other mechanism of the returned radiation is a measure of the partial pressure of a respective blood gas." The technology requires that the probe containing the dye wells be in direct contact with the blood.
U.S. Pat. No. 4,682,985 titled "Fiber Optic Probe for Quantification of Colorimetric Reactions" by D. Costello is a similar technology with the additional feature of a probe which has an overall diameter "sufficiently small to permit the probe to be inserted into living tissue directly" (column 1, lines 12-17). "A colorimetric substance contained in the sample chamber changes colors in response to chemical properties of the chemical to be colorimetrically measured, thereby changing the amount of light transmitted through the sample chamber by the optical fibers." See the abstract of the patent. The patent describes the use of this technology for pH, PCO.sub.2 and PO.sub.2 determinations.
A similar technology to that disclosed by Boiarski and Costello is described for pH determination by S. R. Goldstein et al. in "A Miniature Fiber Optic pH Sensor For Physiological Use," Journal of Biomechanical Engineering, Vol. 102, 141-146. The article describes the concept of using two fiber optic strands to illuminate and remotely sense the color change of a dye indicator contained in a hollow fiber permeable to hydrogen ions.
Another colorimetric technology is described by Gehrich et al. in U.S. Pat. No. 4,989,606. The patent describes an invasive system for sampling small amounts of blood from a patient in a continuous manner. The blood is placed in contact with a "optical sensing element, for example sensing elements based on light fluorescence or absorbance." See column 4, lines 43-45.
Separation by semipermeable membranes.
The direct measurement of the partial pressure of a PO.sub.2 and PCO.sub.2 gas by absorption spectroscopy following separation by a semipermeable membrane is described in U.S. Pat. No. 4,201,222 to T. Hasse. The technology is based on the concept that gas can flow through a barrier until an equilibrium state is reached. If the barrier is made of a material permeable to selected gases then absorption spectroscopy can be used to quantify the amount of gas in the chamber, with the amount of gas present being proportional to the partial pressure of such gas. The specific method of measurement uses a single wavelength determination. Carbon dioxide is measured at approximately 2000 nm and oxygen is measured at 759 nm. Thus, the device described requires insertion into an arterial blood vessel and is not suitable for noninvasive measurements.
Electrode Devices/Sensors
The prior art associated with the measurement of PCO.sub.2 and PO.sub.2 by electrochemical sensors is extensive. A generalized description and overview of this technology can be found in P. Rolfe's article "Review of Chemical Sensors for Physiological Measurement." Biomedical Engineering Centre, University of Oxford, UK. Journal of Biomedical Engineering, 1988, April, 10(2), pages 138-45. The majority of blood gas and electrolyte analyzers used in hospital clinical chemistry laboratory use electrodes. The application of this technology to transcutaneous or noninvasive blood gas determination is most completely described in a series of patents assigned to Radiometer A/S of Denmark. U.S. Pat. Nos. 4,274,418; 4,324,256; and 4,685,465 describe the use of potentiometric and polarographic electrodes for "measurement of the blood gas partial pressures of oxygen and carbon dioxide," (Abstract of U.S. Pat. No. 4,685,465). It is important to note that electrodes measure parameters of the medium in direct contact with the probe. Thus, the partial pressures of oxygen and carbon dioxide measured by the transcutaneous electrodes would be that of the peripheral skin, not arterial blood.
A similar electrode based instrument is described by G. J. Ullrich et al. in U.S. Pat. No. 4,930,506. The technology varies from the Radiometer patents in that the Ullrich invention couples an electrode device with a standard pulse oximeter for continuous determination of peripheral skin PCO.sub.2 and arterial blood oxygen saturation. PCO.sub.2 is measured by immersion of a pH electrode in an electrolyte solution which is then placed in contact with the skin. Oxygen saturation is determined by use of two measured intensities at 650 and 805 nanometers. The algorithm for determination of the oxygen saturation using these two measured intensities is not specified.
In-Vivo pH Measurement Transistors
An area of sensors which has received significant attention over the past decade is the use of ion selective field effect transistors (ISFET). Specifically M. E. Meyerhoff et al., U.S. Pat. No. 4,694,834, B. Oeseburg et al. "Intravascular pH-ISFET, a method of the future," Scand. J. Clin. Lab Invest 1987 (47, Suppl. 188; 31-35), and P. Bergueld "The Development and Application of FET-based Biosensors," Biosensors 2 (1986) 15-33, describe the use of potentiometric ion selective electrodes based on semiconductor technology for the in-vivo continuous determination of pH. The technology is currently limited to pH determination and is invasive.
Semi-Invasive Techniques
A semi-invasive technology for the measurement of pH, PCO.sub.2 and PO.sub.2 is described by M. A. Fostick in U.S. Pat. No. 4,041,932. "Briefly, the technique of the present invention includes the formation of a skin `window` in a small area of a patient by removal of substantially all of the stratum corneum (top dry layer of skin) in the area. Such a window is preferably less than one inch square. An enclosed chamber is positioned tightly against the skin around the window so formed and sealed thereto by sterile grease or adhesives such as the types commercially available for sealing other medical instrumentation elements to the human skin. The chamber and adjacent skin is heated to above normal skin temperature. Gases or fluids are collected in the chamber from the patient through the skin window for a time until equilibrium is reached. The internal portion of the chamber is an extension of the patient's body, at least insofar as the constituent of interest is concerned." See column 53, line 53- column 4, line 1. PH, PCO.sub.2, and PO.sub.2 are then measured by absorption spectroscopy via univariate methodology. Univariate analysis uses the ratio of two wavelengths, one to provide baseline information and a second frequency specific for the analyte of interest. Again, this technology determines certain blood gas parameters (i.e., pH, PCO.sub.2 and PO.sub.2) of peripheral skin, not arterial blood.
Optical or Spectroscopic Determinations
U.S. Pat. No. 4,509,522 by T. J. Manuccia describes the determination of PCO.sub.2 and PCO; invasively in arterial blood, or non-invasively in tissue. The gas concentration is determined by a univariate linear algorithm. The method is described in column 2, lines 35-50 as follows: "For each molecule to be studied, two wavelengths must be transmitted through the blood sample. One wavelength must lie within an absorption band that is characteristic of the molecule (CO: .about.5.13 um) while the other wavelength should be at a nearby wavelength in the IR that is not absorbed by the molecule. By normalizing the magnitude of the absorbed signal to that of the non-absorbed signal, the absolute concentration of the absorbing gas can be determined. Also in this way, the patient-to-patient variations in the optical properties of body tissue and skin are eliminated. The heart of the invention rests on the fact that the various blood gases absorb at discrete wavelengths in the infrared as opposed to their continuous and overlapping absorptions in the visible and near-IR." This last statement implies that the device of Manuccia, et al., would not work in a situation where there are overlapping absorptions. Although this methodology may work well for CO.sub.2 and CO, it would not work well for determination of pH, PO.sub.2, [HCO.sub.3.sup.- ] and O.sub.2 saturation. The spectral regions used for determination of pH, PCO.sub.2, and [HCO.sub.3.sup.- ] overlap extensively as is often the case in the near infrared. Thus, the univariate method described by Manuccia et al. is not applicable to the simultaneous noninvasive determination of all blood gas parameters.
The clinical utility of Manuccia's technology will be limited due to the frequencies used for the PCO.sub.2 and PCO measurement. The frequencies specified by Manuccia (i.e. between 3.0 and 14.0 microns) are in the mid-infrared, an area of the spectral domain in which the light propagation characteristics are not consistent with transmission measurements through the finger, and typically the penetration of light is not to the arterial vasculature. Thus, measurements made will be similar to a peripheral skin determination. To summarize, Manuccia's technology can not measure all blood gas parameters, uses frequencies inconsistent with noninvasive tissue determination and employs an algorithm which will perform poorly in the near infrared frequency region.
Oximetry
The ability to determine arterial blood oxygen saturation in both pediatric and adult populations via oximetry is well known. Pulse oximetry is an accepted method of oxygen determination and has been utilized in clinical medicine for years. All pulse oximeters are based on several governing principles. First, the concentration of blood in a given location of the body varies with each pulse of the heart. With each heart beat a systolic pulse pressure is generated which leads to a maximal expansion (i.e. dilation) of the vascular system. During the resting period of the cardiac cycle (i.e., diastole) there is no pressure generated and the vascular system returns to a minimal size. This variation can be measured with optically based methods, by introducing a light source near the skin and detecting either the reflected or the transmitted light intensity. The light transmitted or reflected during diastole (i.e., the period when the arterial system is at its minimal size) interacts with the skin, fat, bone, muscle and blood. Light transmitted or reflected during systole, (i.e., the period of maximum expansion of the arterial system) interacts with the same skin, fat, bone, muscle, and blood, plus an additional amount of blood which is present due to the expansion of the arterial system. If the diastolic signal is subtracted from the systolic signal the result is a signal which represents the additional amount of blood. The subtraction process removes the interferences created by the interaction of the light with the skin, fat, bone and muscle. The quality and clarity of the subtraction generated signal is related to the amount of additional blood present which, in turn, is proportional to the pulse pressure, (i.e., the difference between systolic pressure and diastolic pressure). See FIG. 2 for a graphical representation of the above process.
All present pulse instruments assess variations in red blood cell concentration by utilizing a light frequency near or at the isobestic point, where optical measurement of pulsatile volume is made independent of oxygen saturation. An isobestic wavelength is one which changes only with blood concentration but does not change intensity with oxygen saturation. Consequently, such a wavelength (typically in the range of 800-850 nm) intentionally eliminates information about oxygen saturation and establishes a reference. A second wavelength in the red portion of the spectrum, which is sensitive to oxygen saturation, is detected by either a transmission or reflection sampling technique. By using the isobestic wavelength as a reference and by comparing its spectral intensity to the intensity of the second wavelength in the red portion of the spectrum, it is possible to determine the oxygen saturation of the arterial blood non-invasively.
Spectroscopic Determination of pH in Non-Biological Systems
Optical determination of pH in non-biological systems has been demonstrated by several investigators. Two representative articles are "Near-infrared Spectrometric Determination of Hydrogen Ion, Glucose and Human Serum Albumin in a Simulated Biological Matrix," by Drennen et al. and "Measurement of caustic and caustic brine solutions by spectroscopic detection of the hydrogen ion in the near-infrared region, 700-1150 nm", by M. K. Phelan, one of the co-authors of current application.
With specific reference to pH determination, Drennen et al. describe a process for quantitative spectroscopic measurement using smoothed second-derivative spectra with multivariate analysis by principle component regression (PCR). Nineteen different sample solutions, with pH values ranging from 4.5 to 9.25 were scanned from 1100 to 2500 nm. The pH variation in the sample set was achieved by addition of appropriate amounts of acid and base (i.e. HCl or NaOH). Although the paper does describe the quantitative spectroscopic determination of pH by multivariate analysis, the solutions were extremely simple with the pH being the sole source of variation. This is sharp contrast to determination of pH in blood or tissue which are extremely complex systems with multiple varying parameters, (i.e., the remaining four blood gas parameters). Also, the pH range measured by Drennen et al. is outside the range consistent with human survival and the frequency region used is not compatible with noninvasive transmission measurement. Specifically, frequencies greater than 1450 nm are strongly attenuated by water and transmission through a significant amount of tissue is not possible.
Phelan et al. demonstrated measurement of hydrogen ion concentration in caustic (sodium hydroxide) and caustic brine (sodium hydroxide and sodium chloride) solutions. These investigators used the frequency region from 700-1150 nm with subsequent analysis of the resulting spectra by multiple linear regression and partial least squares. As above, it's important to emphasize that the system studied is not biological, the pH variation is far outside that of normal physiology, and is not nearly as complex as found in biological systems.
Background on Spectral Analysis Algorithms
Optical measurements in whole blood following reactions with enzymes and/or reagents are commonly employed in the clinical chemistry laboratory. The use of spectroscopic techniques with multiple wavelengths for such a determination is much less common. Further, it is essential to realize that all prior noninvasive monitors, specifically Manuccia, et al., and the majority of prior art pulse oximeters used 3 or less measured intensities and one or two variables for analysis. Methods that simultaneously use two or more variables are known as multivariate methods. Thus, while Manuccia et al and the above described pulse oximeters do utilize optical measurement techniques, the algorithms used for analysis are not as powerful or sophisticated as those utilized herein.
A simple illustration of the increased capability of multivariate methods in component concentration determination is provided by FIGS. 3. In FIG. 3A one can see that an impurity component, whose spectrum overlaps that of the analyte, can affect the spectrum of the analytic band. Therefore, the accuracy of the analysis will suffer when the analysis is performed at a single wavelength .nu..sub.1 or when rationing .nu..sub.1 to a reference wavelength. The measured absorbance, A.sub.m, at the analysis wavelength, .nu..sub.1, for a sample containing the impurity is different than the true absorbance, A.sub.t, of the analyte at that wavelength. If the calibration curve in FIG. 3B is from spectra of samples containing no impurity, then the presence of the impurity in the sample will yield an apparent concentration that may be quite different from the true concentration. This error will remain undetected if the intensity was measured at only one wavelength. If the impurity is included in the samples, a calibration plot similar to that in FIG. 3B will exhibit large scatter among the data, and the result will be both a poor calibration curve and concentration estimates that have poor precision for the unknown samples. However, with analysis at more than one wavelength, not only can the presence of the impurity be detected, FIG. 3C, but if its presence is included in the calibration, quantitative analysis of the analyte is possible with multivariate calibration methods, even if the impurity and its concentration are unknown.
An indication that the unknown is different from the set of calibration samples not containing the impurity is obtained by plotting the absorbance of the calibration samples and the unknown sample spectra at two frequencies selected for analysis. As exhibited in FIG. 3C, the spectrum of the sample containing the impurity (indicated by "x") is obviously different than that of the calibration spectra (i.e., it is an outlier). Outliers are those samples or spectra among either the calibration or unknown data that do not exhibit the characteristic relationship between composition and spectra of the other calibration samples. The sensitivity in detecting outliers is increased by increasing the number of frequencies included in the analysis. The number of independently varying impurities that can be simultaneously accounted for in the analysis is also increased by increasing the number of frequencies utilized.
Accurate univariate methods are dependent upon the ability to identify a unique, isolated band for each analyte. Multivariate methods can be used even when there is overlap of spectral information from various components over all measured spectral regions. Unlike univariate methods, multivariate techniques can achieve increased precision from redundant information on the spectra, can account for base-line variations, can more fully model nonlinearities, and can provide outlier detection.
The general approach that is used when statistical multivariate methods are applied to quantitative spectroscopy problems requires calibration in which a mathematical model is generated relating analyte concentrations to reference spectra. See FIG. 4. This calibration model can then be used for prediction of concentrations in unknown samples. The spectra of a series of calibration standards are first obtained, such that the spectra span the range of variation of all factors which can influence the spectra of future unknown samples. Assuming that the calibration uses samples that contain all the components expected in the unknown samples and spans their expected range of variation, the calibration will be able to empirically account for (or at least approximate) non-ideal behavior in Beer's law, independent of the source of the non-ideal behavior. Nonlinearities may arise from spectroscopic instrumentation, dispersion, or intermolecular interactions. As used in this application "nonlinear" refers to any deviation in Beer's law or the inverse Beer's law relationship (i.e., which cannot be modeled with the standard linear expression y=mx+b; where y represents the dependent variable, x is the independent variable, and m and b are, respectively, the slope and intercept).
Once the empirical calibration relating spectra and component concentrations has been performed, then the spectrum of the unknown sample can be analyzed by a multivariate prediction step to estimate the component concentrations or properties. If the calibration samples are truly representative of the unknown sample, then the result of the analysis will be an estimate of analyte concentration. In addition, spectral residuals (i.e., the difference between measured and estimated spectra) can be used to determine if the unknown sample spectrum is contained within the range spanned by the calibration samples. If the unknown sample is not representative of the calibration samples (i.e., is an outlier), spectroscopic interpretation of the residuals can often be made to determine the source of any differences between unknown and calibration samples. See Haaland, David M.: "Multivariate Calibration Methods Applied to Quantitative FT-IR Analysis" in Practical Fourier Transform Infrared Spectroscopy, Industrial and Laboratory Chemical Analysis, Edited by J. R. Ferraro and K. Krishman, Academic Press, Inc. 1990. Not only do multivariate statistical methods provide enhanced analysis of component concentrations, but such multivariate methods have also recently made possible the estimation of physical and chemical properties of materials from their spectra. Such multivariate statistical methods have been used in the analysis of salt water, peas, glucose, and thin-film dielectrics.
The use of multivariate analysis in noninvasive medical monitoring is best described in U.S. Pat. No. 4,975,581 to M. R. Robinson, K. J. Ward, R. P. Eaton and D. M. Haaland and current pending U.S. patent application Ser. No. 07/729,452, titled "Oximeter for Reliable Clinical Determination of Blood Oxygen Saturation in a Fetus" by M. R. Robinson, D. M. Haaland and K. J. Ward. U.S. Pat. No. 4,975,581 discloses a method and apparatus for, particularly, quantitatively determining the amount of glucose in a human.
Co-pending patent application Ser. No. 07/729,452 describes a fetal oximeter which is designed to:
A. Overcome the limitations of prior art oximeters, including their inability to obtain information at a variety of wavelengths simultaneously, and the limitation inherent in the time necessary for the intermittently energized light sources in such prior art oximeters to reach the required brightness and stability.
B. Utilize multiple frequencies with simultaneous sampling, employ an algorithm which can signal average over the recorded frequencies and model nonlinearities over the entire clinically observed blood oxygen saturation range and which is suitable for noninvasive measurements in the fetal environment.
C. Determine if a sample's spectrum and subsequently determined oxygen saturation value (from either the calibration set or the fetus being monitored) is representative of the calibration samples.
This last object is crucial for the implementation of an accurate and reliable clinical fetal monitor. Identifying and removing outlier samples from the calibration set can drastically improve the accuracy and precision of the subsequent predictions. Identification of outliers among the unknown samples provides information for evaluating the validity of the fetal blood oxygen saturation determination. This ability is especially important in this medical application because the consequences of hypoxia on the fetus can result in death or lifelong disability.
A number of multivariate calibration methods are available for quantitative spectral analyses. Many of these have been reviewed by D. M. Haaland, supra. These include PLS, PCR, CLS, MLR, Q-matrix, Kalman filtering, and cross-correlation. In addition, ridge regression, continuum regression, and neural networks are other possible multivariate methods that can be used in quantitative spectral analysis.
Multivariate methods which are well suited for analysis of blood gas parameter spectroscopic data are those that model the spectra using an inverse Beer's law model, such as principal component regression (PCR) or partial least squares (PLS). An advantage of this multivariate approach is that the nonlinearities in the spectral response to changes in composition can be accommodated without the need for an explicit model. PLS and PCR methods are capable of achieving accurate and precise results in the presence of linear and nonlinear dependencies in the absorbance spectrum at various frequencies. Thus, an entire spectral region can sometimes be used in multivariate analysis without the requirement that the spectroscopist choose an optimal set of wavelengths for the analysis. Similarly, these methods of computation are not sensitive to linear dependencies introduced by over sampling of information at many frequencies in the construction of the calibration samples. See Cahn, et al., "Multivariate Calibration of Infrared Spectra for Quantitative Analysis Using Designed Experiments". Applied Spectroscopy 1988 Vol. 42 No. 5 p. 865.
Continuum regression comprises an infinite-member family of methods for multivariate calibration. PLS and PCR are individual members of the continuum regression family. See, M. Stone, and R. J. Brooks (1990), "Continuum Regression: Cross-validated Sequentially Constructed Prediction Embracing Ordinary Least Squares, Partial Least Squares and Principal Components Regression," Journal of the Royal Statistical Society B., 52, pp. 237-269.
Two or more analytes can be calibrated or analyzed simultaneously by using a global PLS method called PLS2. In practice PLS2 tends to underperform PLS1 (analytes calibrated sequentially) primarily because model complexity is fixed for all analytes. Also, it is difficult to come up with a necessary metric that combines calibration errors across wildly different analytes, which is akin to adding apples and oranges. See, Lindberg W. Pesson, J. A. Wold, S. (1983), Analytical Chemistry, 55, p. 643.
Ridge regression is another multivariate calibration method which has been used in non-medical situations in which the intensities at different spectral frequencies exhibit significant collinearity and the number of calibration samples exceeds the number of spectral frequencies. Martens and Naes, "Multivariate Calibration," John Wiley: Chichester, (1989), showed that ridge regression is mathematically similar to PCR, but cannot be described explicitly by data compression. Hoerl et al., Practical use of ridge regression: a challenge met, "Applied Statistics" 34, 114-120, (1985), showed that ridge regression was a viable competitor to multiple linear regression in the context of predicting percent protein in wheat samples by using reflectance in the near infrared region. Naes et al., Comparison of lineal statistical methods for calibration of NIR instruments, "Applied Statistics" 35, 195-206, (1985), concluded that ridge regression is a viable competitor to PLS and PCR when the number of spectral frequencies approaches the number of calibration samples.
Another type of multivariate algorithm gaining wide acceptance is a pattern recognition technique using what are called neural networks. Weights are applied to the inputs, which determines the signal strength. The sum of the inputs at that neuron determines the strength of the neuron. The weighted sum is transformed with a linear or nonlinear transfer function, the most popular transform being the sigmoid function. This transfer function determines the output of the signal, depending on the gain that is set. All neurons are interconnected, but pass data only one way, as the brain does. The output signal can be transferred to several different neurons, each of which has its own weight. The network "learns" the weights of the output signal at each neuron, optimizing the weights to achieve the "correct responses" (i.e. the reference calibration values). Like other multivariate calibration methods, neural networks learn from the input they are given. They have the potential advantage that they can explicitly model nonlinearities. However, they also tend to be more susceptible to overfitting, and slower to compute, and are more difficult to interpret than PLS, PCR, and MLR.
The applicants recognize that both the preferred embodiment of U.S. Pat. No. 4,975,581 and co-pending application Ser. No. 07/729,452 utilize the partial least square algorithm (PLS). However, the reasons for utilizing PLS and the other multivariate algorithms in the invention disclosed and claimed herein is quite different from the reasons it was utilized in the above described patent and application. For noninvasive glucose determination, the limiting factor in measurement is the lack of information available. The determination of a blood analyte, such as glucose, requires a very high signal-to-noise ratio and a sophisticated algorithm for extraction of a minuscule amount of information (glucose is, normally, 0.1 weight percent of blood). In the case of a pulse oximeter suitable for fetal monitoring, the information is abundant (i.e., babies that are profoundly hypoxic are blue), but the environment of operation is extreme. The reflected light-oxygen saturation relationship is highly nonlinear, the signal for analysis is extremely noisy and interfering background components must be removed by correlating with the pulsating blood.
In contrast to the foregoing, the rationale for using multi-variate analysis in the present application of noninvasive blood gas determination is to enable accurate determination of blood gas parameters where the information content in the spectral domain overlaps and where the infrared patterns for pH, PCO.sub.2, PO.sub.2 and [HCO.sub.3.sup.- ] are small or do not exist in the absence of interactions with water and other blood or tissue components. Examination of FIG. 10 shows that the regions of spectral information for the various components overlap extensively. This is especially true for pH which does not exhibit a strong correlation in any specific region. The problem of differentiating bicarbonate from carbon dioxide is also difficult as evidenced by their similar correlation curves.
The use of visible and infrared spectroscopy for the noninvasive determination of blood gas parameters is not obvious. In fact "at first glance, the determination of pH by infrared spectroscopy is so implausible as to seen ridiculous." "Salinity determination using NIRH," T. Hirschfeld, Applied Spectroscopy, Volume 39, Number 4, 1985. Not only does water have exceptionally strong absorption bands, but H+ and O.sub.2 sat. have no absorption bands of their own in the near infrared.
Infrared spectroscopy obtains quantitative and qualitative information from the vibrational motion in molecules. Each type of chemical bond in a molecule will absorb different frequencies of infrared energy, giving rise to the characteristic patterns seen in an infrared spectrum. These patterns, called absorption bands, change in magnitude with concentration. Traditional methods of quantitative spectroscopy correlate band height or the area of a band to the concentration of the species under study. In the present application of infrared spectroscopy, characteristic infrared patterns for each species under study (pH, O.sub.2, CO.sub.2, [HCO.sub.3.sup.- ] are small or do not exist when not interacting with other components. However, these species do have an effect on species that do absorb, specifically hemoglobin and water. Hydrogen ion, being an ion rather than a molecule, does not have infrared bands. However, hydrogen ions will bind to other species in solution that are infrared active, thus a correlation for pH can be based on secondary spectroscopic effects. Oxygen, although a molecular species, does not have infrared bands. However, it will also interact with other species that are infrared active and produce a change in the spectra. In particular, oxygen reacts with hemoglobin, producing a marked change in the infrared spectra of hemoglobin between 600 and 1000 nm. This reaction is nonlinear, however, and quantitative models must account for this nonlinearity. For CO.sub.2, and [HCO.sub.3.sup.- ], near infrared spectral absorbances are small. CO.sub.2 can be quantitated easily in the mid-infrared region. [HCO.sub.3.sup.- ] also has bands in the mid infrared region. But in the near infrared region, CO.sub.2 and [HCO.sub.3.sup.- ] absorbance are small compared to the much larger effect of hemoglobin and proteins. Again, secondary effects must be studied. Thus, accurate measurement of the various blood gas parameters is difficult due to the small absorbances and/or secondary effects resulting from concentration changes. These differences necessitate the use of multivariate analysis.
The clinical utility of pulse oximetry is well established. The clinical utility of a noninvasive blood gas monitor, (for the simultaneous determination of pH, PCO.sub.2, PO.sub.2, [HCO.sub.3.sup.- ] and O.sub.2 saturation) is clearly desirable and the technology for realization of such a monitor as well as data utilizing the technology is disclosed herein. Continuous monitoring and real time (i.e., analysis of the data as it is acquired) is desired, as it would enable the physician to identify peaks, troughs and trends as they are occurring in the patient. Such monitoring would be of significant benefit when a patient's cardiopulmonary status is changing rapidly.
It is an object of the present invention to provide an instrument which will represent a remarkable improvement in blood gas monitoring technology by:
A. Providing noninvasive blood gas monitoring which can determine all blood gas parameters in arterial blood and/or tissue.
B. Providing continuous determination of all blood gases in real time; and
C. Having the ability to provide the physician with a measure of validity or assurance of accuracy by employing outlier detection methods.
The ability to determine inaccurate results is extremely important, especially when caring for the critically ill patient.
It is an object of the present invention to determine the blood gas parameters in either human tissue. In the case of tissue determination, the light will interact with tissue in both the dermis and epidermis. If the light is transmitted through, for instance, the finger, the optical determination will measure the blood gases of all the components that are irradiated by the light. Total tissue blood gas determination is not currently used in clinical medical practice due to lack of availability of such information. However, total tissue determination may be a better measure than arterial blood gas measurement because the physician is interested in knowing how well the tissue is being perfused by the patient's cardiopulmonary system. If the tissue in an extremity is being well perfused then the physician could reasonably assume that more vital and internal organs were also being perfused at an adequate rate, (i.e. liver, kidney, spleen and brain).
It is an additional object of the present invention to determine blood gas parameters in arterial blood. The method of sampling during the systolic and diastolic portions of the cardiac cycle enables determination of the pulse blood spectra. This spectra can be subsequently analyzed by multivariate algorithms for determination of blood gas parameters. Thus, the present invention enables measurement of blood gas parameters in arterial blood noninvasively.
In the case of the present invention, it is an object to use wavelengths in the 500-2400 nm range to determine arterial blood gas parameters. As several components are determined, measured intensities at several wavelengths will be required. Each parameter to be measured often requires at least one measured intensity for determination and each spectroscopically interfering substance will also usually require measurement of an intensity for compensation of its interference. Thus, determination of multiple components may require measurement of three or more wavelengths.
An additional advantage of the methodology of the present invention is the ability to report all blood gas parameters. The various parameters can be measured directly or calculated from well established equations. The relationship between pH, PCO.sub.2, and [HCO.sub.3.sup.- ] is described by the Henderson-Hasselbach equation: ##EQU1## The Henderson-Hasselbach equation allows for determination of two components with calculation of the third.
Additionally PO.sub.2 can be calculated from O.sub.2 sat. and vice versa. O'Riordan et al. compared various calculation algorithms and assessed their accuracy relative to normal human data. See, J. F. O'Riordan, T. K. Goldstick, L. N. Vida, G. R. Honig, and J. T. Ernest, "Modelling whole blood oxygen equilibrium; comparison of nine different models fitted to normal human data", Advances in Experimental Medicine, Vol 191, pp 505-522, 1985. The concurrent use of pH in these calculations to more accurately assess the P.sub.50 value may improve overall calculation results.